Multivariate ToF-SIMS image analysis of polymer microarrays and protein adsorption

Abstract

The complexity of hyperspectral time of flight secondary ion mass spectrometry (ToF-SIMS) datasets makes their subsequent analysis and interpretation challenging, and is often an impasse to the identification of trends and differences within large sample-sets. The application of multivariate data analysis has become a routine method to successfully deconvolute and analyze objectively these datasets. The advent of high-resolution large area ToF-SIMS imaging capability has enlarged further the data handling challenges. In this work, a modified multivariate curve resolution image analysis of a polymer microarray containing 70 different poly(meth)acrylate type spots (over a 9.2 × 9.2 mm area) is presented. This analysis distinguished key differences within the polymer library such as the differentiation between acrylate and methacrylate polymers and variance specific to side groups. Partial least squares (PLS) regression analysis was performed to identify correlations between the ToF-SIMS surface chemistry and the protein adsorption. PLS analysis identified a number of chemical moieties correlating with high or low protein adsorption, including ions derived from the polymer backbone and polyethylene glycol side-groups. The retrospective validation of the findings from the PLS analysis was also performed using the secondary ion images for those ions found to significantly contribute to high or low protein adsorption.

Secondary ion mass spectrometry imaging and multivariate data analysis reveal co‐aggregation patterns of Populus trichocarpa leaf surface compounds on a micrometer scale

“…Such an analysis is extremely tedious to carry out as well as difficult to draw inferences from when performed manually. The total number of TOF‐SIMS spectra acquired – where each spectrum corresponds to a pixel – makes interpretation difficult, leading to the possibility that much significant information related to hundreds of mass peaks remains hidden (Hook et al ., ). It has also been observed that within a typical TOF‐SIMS spectrum, multiple peaks are generated from the same surface molecules, and their relative yields are often related.…”

The impact of detergents on the tissue decellularization process: A ToF-SIMS study

“…Time of flight secondary ion mass spectrometry (ToF-SIMS) is an analytically sensitive, information-rich surface analytical technique that has been used to investigate various biological samples, from the distribution of proteins and lipids in brain tissue [32] to high throughput screening of polymer microarrays as cell substrates [33–35]. Recently, ToF-SIMS was utilized to identify differences in cell-secreted matrices [36], to confirm adsorption of complex extracellular matrix coatings [37] and to analyse variances in the surface composition of decellularized tissues from different origins [38, 39].…”

ToF-SIMS analysis of a polymer microarray composed of poly(meth)acrylates with C6derivative pendant groups

“…Automated surface analysis of large sample sets has been achieved for water contact angle measurements, X‐ray photoelectron spectroscopy, atomic force microscopy, surface plasmon resonance and time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) . ToF‐SIMS has been widely used for studying polymeric systems, and when coupled with multivariate analysis has proven to be particularly useful for establishing correlations between the surface chemistries of a library of materials with various properties such as water contact angle and cell attachment . Whilst these correlations eloquently demonstrate a relationship between surface chemistry and the interfacial performance of the materials, the models themselves are difficult to interpret as they typically feature an abundance of small ion fragments that are derived from multiple, if not all, materials present in a study and are thus difficult to assign to specific chemical functionalities or properties.…”